(SoE) School of Engineering

Shiv Nadar University is a comprehensive, multidisciplinary, research-focused, and student-centric University offering a full range of academic programs at the undergraduate, postgraduate and doctoral level. With state-of-the-art infrastructure, the University comprises of academic wings, sophisticated labs, international standard sports facilities, amphitheaters, auditorium, conference rooms and smart classrooms. The University&rsquo;s goal is to become internationally recognized for the quality of its research and creative endeavors and their applicability to improving quality of life, generating new insights and expanding the boundaries of human knowledge creativity. Committed to excellence in teaching, research and service, the University aims to serve the higher education needs of India and the world beyond.

Shiv Nadar University

Here, we report a facile approach for the development of unique nanoporous MnO2-Cu architecture through a combination of severe surface deformation and dealloying. The severe surface deformation of Cu-Mn alloy prior to selective dealloying resulted in the precipitation of nanoporous MnO2 in the Cu-rich substrate. The in situ grown nanoporous MnO2-Cu architecture demonstrated an areal capacitance of 2.8 F/cm2 at a current density of 5 mA/cm2 and exhibits an excellent cyclic stability of 95% retention for 4000 cycles at 15 mA/cm2 current density. The MnO2-Cu composite structure showed small charge transport resistance of 1.9 Ω as determined using impedance spectroscopy. The asymmetric supercapacitor fabricated using nanoporous MnO2-Cu as anode and reduced graphene oxide as cathode delivers specific energy of 5.55 Wh kg−1 at a specific power of 249.75 W kg−1. The superior performance of nanoporous MnO2-Cu architecture was attributed to its unique microstructure that ensures high surface area, small internal resistance with rapid charge transport. The current approach can be applied to different material systems and is potentially transformative in the emerging field of advanced supercapacitors. © 2021 Elsevier Ltd

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Mechanical Engineering

Journal of Energy Storage

Facile synthesis of MnO2-Cu composite electrode for high performance supercapacitor

This paper primarily focuses on the design and analysis of uniform circular array of four planar horn antenna elements with a perspective of optimizing them at frequency of 70 GHz. The four horn antenna elements are placed at an angle separation of 90degrees. The four antennas are connected via a coaxially fed four-port equal power divider circuit. The array is designed for millimeter wave frequency (60-90 GHz) application. Aluminum is used as conductor for radiating elements and ground while polyimide was used as the substrate. The proposed array has very sensitive feed line width that is able to change the resonance frequency. The proposed antenna design is simulated and analyzed for Multi Input Multi Output (MIMO) and Orbital Angular Momentum (OAM) applications in E band. © 2021 IEEE.

Electrical Engineering

2021 International Conference on Intelligent Technologies, CONIT 2021

E-Band [70GHz] Uniform Circular Array of Planar Horn Antenna for MIMO/ OAM Applications

In this work, an underlap structure of tunneling field-effect transistor (TFET) containing electrolyte/watery solution is examined to enhance the Nernst limit (59 mV/pH) of sensitivity. After incorporating the electrolyte medium in TFET, effect of pH variation on device characteristics such as drain current vs front gate voltage, voltage sensitivity, and current sensitivity are investigated. The interface charge density at the oxide-silicon interface of TFET is obtained as a function of electrolyte pH from physics-based modelling. Voltage sensitivity value 180 mV/pH that is greater than three times of Nernst limit of 59 mV/pH and current sensitivity value that is more than one decade per pH are observed for TFET based sensor. In order to validate the results, models used in TFET are well-calibrated with experimental data and the result of TFET are compared with inversion mode (IM) device. Results show that TFET gives superior performance than IM device; hence an underlap TFET can be a promising alternative for the next generation biosensor. © 2001-2012 IEEE.

IEEE Sensors Journal

Crossing the Nernst Limit (59 mV/pH) of Sensitivity through Tunneling Transistor-Based Biosensor

The seismicity of the National Capital Region (NCR) of India increased significantly over the last decade. Communities in the NCR face significant exposure to damaging seismic events, and the seismic risk arises not only from the region’s proximity to the Himalayan mountains, but also from the socioeconomic vulnerabilities in its communities and the current capacities of different localities to respond to and recover from any unforeseen large seismic event. GIS-based spatial distribution of exposure to seismic hazards (SH) can help decision-makers and authorities identify locations with populations at high seismic risk, and to prepare risk-mitigation plans. Socioeconomic vulnerability (SeV) studies serve as a basis for quantifying qualitative measures. For this purpose, in the present study, the hazard of place (HoP) model is used to assess SeV to seismic hazards in the NCR. Social indicators like age, gender, literacy, family size, built environment, etc., comprising a total of 36 variables, are used to assess a socioeconomic vulnerability index (SeVI) based on factor and principal component (PCA) analyses. Based on PCA, 20 variables were retained and grouped into four factors: socioeconomic status, employment status, building typology, and family size. Ground-motion parameters, estimated from probabilistic seismic hazard assessment, are integrated with the socioeconomic vulnerability index to quantify exposure to seismic hazards. The spatial distributions in the produced socioeconomic-vulnerability index and seismic–hazard–exposure maps highlight the critical areas. The results reveal that areas of low literacy, high unemployment, and poor housing condition show moderate-to-high vulnerability. The south-eastern region of the study area is assessed as a high-risk zone by an integrated SeV–SH risk matrix. The results of this study emphasize the importance of the socioeconomic vulnerability component of disaster risk–reduction programs, from a holistic perspective, for the areas with high seismicity. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.

Civil Engineering

Fulltext

Sustainability (Switzerland)

Assessment of the socioeconomic vulnerability to seismic hazards in the national capital region of India using factor analysis

Porosity plays a significant role in concrete strength and durability. It also imparts the randomness in paste and aggregate bonding in cement concrete composite. The paper presents the optical evaluation and analysis of pores in cement mortar sample. The analysis has been done using microscopic images of a thin section of the cement mortar obtained from optical microscope. The mortar samples were prepared by varying its water–cement ratio, different batching process and substituting supplemental cementious material. The microscopic images have processed through ImageJ software for pore size evaluation and its distribution the surface of cement mortar sample. The classification of pores has been made based on its size and their formation for different water–cement ratio, batching processes and usage of cementious material. The overall results obtained through optical evaluation have satisfactory variation and significance in order to understand the progress of hydration and its conductive properties through non-destructive ways. © 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Lecture Notes in Mechanical Engineering

Pore Evaluation and Distribution in Cement Mortar Using Digital Image Processing

Manipulation of images, videos and audios using face edit apps and web services have long been in use, since decades but recent advances in deep learning has led to rising AI generated fake images and videos with swapped faces, lip synced audios and puppet masters, popularly known as Deepfakes. Generated primarily using one of the following two approaches namely, Autoencoders and Generator Adversarial Networks which rests on trained deep neural networks, deepfakes offer unprecedented challenges. The degree of realism achieved by deep learning powered deepfakes increases with increasing amounts of data i.e, fake images and videos readily available on the internet at disposal to train GANs. Deepfake algorithms create media leaving a bare margin of difference between the authentic or original source and the forged or deepfaked targets. Thus, new mechanisms and techniques to detect and filter out such deepfakes is the need of the hour.This paper exploits two powerful deep learning based CNN architectures namely, Inception-Resnet-v2 and XceptionNet for detecting the deepfakes. The proposed approach not only outshines the existing approaches in terms of efficiency and accuracy but also offers the best in terms of the given space and time complexity. © 2021 IEEE.

Computer Science and Engineering

Proceedings - 5th International Conference on Computing Methodologies and Communication, ICCMC 2021

Demystifying deepfakes using deep learning

One of the prime commodities in modern civilization is energy. The amount of energy consumption has become the indicator for the standard of living and the degree of industrialization. People use fossil fuels to meet nearly all of their energy needs, such as powering vehicles, producing electricity for light and heat and running factories, thus greatly exhausting the fossil fuel reserves along with polluting the environment with greenhouse gases. Renewable energy sources are viable alternatives, and among the various types of renewable energy sources available, wind energy is the sector which has a lot of untapped potential. Our objective is to improve the efficiency of a Savonius-type vertical-axis wind turbine (VAWT) which currently has the least efficiency among existing wind turbine designs. Savonius turbines have a very compact structure and can run at low wind speeds which are desirable characteristics for commercial-scale power production. This research paper focuses on improving the efficiency of Savonius wind turbine. Since Savonius-type wind turbines are drag-based wind turbines, we need to reduce the impulsive force acting on the negative face in order to increase the drag difference between the positive and negative side of the rotor blades thereby improving the efficiency of the turbine.&nbsp;Our proposition for attaining higher efficiency is by incorporating the concept of dimples (inspired from golf ball) on the negative side of the rotor blade and tubercles (inspired from whales) on the leading edge of the rotor blade. Dimples reduce the amount of wake region in the case of golf ball by increasing turbulence which is one of the desirable characteristics in the case of Savonius wind turbine. Tubercles help in reducing the wake region behind the rotor blades by increasing the turbulence of air near the surface of the rotor thereby improving the efficiency of the turbine. © 2021, Springer Nature Singapore Pte Ltd.

Performance Enhancement of a Savonius Vertical Axis Wind Turbine with Bio-Inspired Design Modifications

Road networks are permanent manmade features altering the landscape structure and subsequently influence regional landscape ecology. Taking south-western foothills of Central Himalaya, as a case, this study assessed the spatio-temporal variations in landscape structure and landscape ecological risk (LER) influenced by the road network and topography. The relationship between LER and accessibility factors (distance to different road-types and road kernel density) and topographical factors (elevation and slope) were explored using ordinary least square (OLS) regression and geographically weighted regression (GWR) model. Our results indicate that high-risk LER zones are closer to the road network. This is also in conjunction with increasing built-up areas adjacent to the road network. Regression analysis using GWR model better explained the relationship between LER (dependent variable) and distance from different road-types (independent variables) as compared to OLS with a significant correlation at 1\% confidence interval. The spatial variations in the interrelation between dependent and independent variables were explained using quantified coefficients estimated by the GWR model. The estimation and visualization of spatial associations between landscape structure, LER, and road network provided in our study can act as a baseline for developing a guideline for sustainable infrastructure development and management of ecologically vulnerable landscapes across the tropical world. © 2020 Taylor &amp; Francis Group, LLC.

Human and Ecological Risk Assessment

Spatio-temporal variations in landscape ecological risk related to road network in the Central Himalaya

In this work, the steam gasification of mixed food waste was carried out with torrefaction as pretreatment. Torrefaction was carried out at various temperatures; 230 °C, 260 °C, and 290 °C and for one-hour residence time. Improvement in physico-chemical properties of food waste by torrefaction was studied using proximate, elemental, and compositional analysis. Additionally, the effect of torrefaction on mass yield, energy yield, mass density and energy density was presented. Gasification was then carried out using torrefied food waste as biomass with steam as a gasification agent at 700 °C. The steam flow rate was kept at 0.625 mL/min with a steam to biomass ratio of 1.25. The resulting syngas was characterized for syngas yield, syngas composition, H2yield, and high heating value (HHV). It was found that syngas yield and H2field varied from 0.95 to 3.49 m3/Kg and 0.6 to 2.15 m3/Kg respectively from gasification of food waste torrefied at different temperatures. The highest HHV of syngas was found to be 12.19 MJ/Nm3. Cold gas efficiency and carbon conversion efficiency were also determined to evaluate the performance of proposed pretreatment on steam gasification. © 2020 Georg Thieme Verlag. All rights reserved.

Chemical Engineering

Journal of Environmental Chemical Engineering

Steam gasification with torrefaction as pretreatment to enhance syngas production from mixed food waste

In this paper, the reflection of acoustic waves obliquely incident onto various fluid–solid interfaces is investigated. This study aims to measure the influence of solid material properties on the acoustic attenuation magnitude, for oblique incidence at varying frequencies. A detailed comparison is documented by plotting the reflection coefficient curve for each case, while meticulously varying the porosity &amp; permeability of the poroelastic solid. Further attention is focused on identifying the shift in the pseudo-Brewster angle and the dip in the reflection coefficient minima for the aforementioned permutations in attenuation to measure its acoustic response. To enable this, the reflection and absorption of acoustic plane waves incident upon half-space and two-layer interfaces are modelled (by including viscous and thermal losses) and studied. Based on the findings, the study draws significant conclusions on the strong influence of the propagating media on the shape of the reflection coefficient curve and the relative influence of the permeability, porosity, and driving frequency on the pseudo-Brewster angle and the curve minima. © 2020